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Data from both a randomized trial and an observational study are sometimes simultaneously available for evaluating the effect of an intervention.
A james-stein type estimator for combining unbiased and possibly biased estimators
Edwin J Green and William E Strawderman · 1991
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Estimation of regression coefficients when some regressors are not always observed
James M Robins, Andrea Rotnitzky, and Lue Ping Zhao · 1994
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Design of the women’s health initiative clinical trial and observational study
G Anderson, S Cummings, LS Freedman, C Furberg, M Henderson, SR Johnson, L Kuller, J Manson, A Oberman, RL Prentice, et al · 1998
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Improved estimation for multiple means with heterogeneous variances
Edwin J Green, William E Strawderman, Ralph L Amateis, and Gregory A Reams · 2005
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Combined postmenopausal hormone therapy and cardiovascular disease: toward resolving the discrepancy between observational studies and the women’s health initiative clinical trial
Ross L Prentice, Robert Langer, Marcia L Stefanick, Barbara V Howard, Mary Pettinger, Garnet Anderson, David Barad, J David Curb, Jane Kotchen, Lewis Kuller, et al · 2005
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Subgroup analysis in randomised controlled trials: importance, indications, and interpretation
Peter M Rothwell · 2005
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A semiparametric model selection criterion with applications to the marginal structural model
M Alan Brookhart and Mark J Van Der Laan · 2006
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Combined analysis of women’s health initiative observational and clinical trial data on postmenopausal hormone treatment and cardiovascular disease
Ross L Prentice, Robert D Langer, Marcia L Stefanick, Barbara V Howard, Mary Pettinger, Garnet L Anderson, David Barad, J David Curb, Jane Kotchen, Lewis Kuller, et al · 2006
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The adaptive lasso and its oracle properties
Hui Zou · 2006
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Demystifying double robustness: A comparison of alternative strategies for estimating a population mean from incomplete data
Joseph DY Kang, Joseph L Schafer, et al · 2007
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Higher order influence functions and minimax estimation of nonlinear functionals
James Robins, Lingling Li, Eric Tchetgen, Aad van der Vaart, et al · 2008
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Generalizing evidence from randomized clinical trials to target populations: The actg 320 trial
Stephen R Cole and Elizabeth A Stuart · 2010
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Estimating treatment effect via simple cross design synthesis
Eloise E Kaizar · 2011
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The use of propensity scores to assess the generalizability of results from randomized trials
Elizabeth A Stuart, Stephen R Cole, Catherine P Bradshaw, and Philip J Leaf · 2011
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On the covariate-adjusted estimation for an overall treatment difference with data from a randomized comparative clinical trial
Lu Tian, Tianxi Cai, Lihui Zhao, and Lee-Jen Wei · 2012
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Confounding and effect modification: distribution and measure
Tyler J VanderWeele · 2012
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Incorporating data from various trial designs into a mixed treatment comparison model
Susanne Schmitz, Roisin Adams, and Cathal Walsh · 2013
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Combining observational and experimental data to find heterogeneous treatment effects
Alexander Peysakhovich and Akos Lada · 2016
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New methods for treatment effect calibration, with applications to non-inferiority trials
Zhiwei Zhang, Lei Nie, Guoxing Soon, and Zonghui Hu · 2016
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Doubly robust uniform confidence band for the conditional average treatment effect function
Sokbae Lee, Ryo Okui, and Yoon-Jae Whang · 2017
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Transportability of trial results using inverse odds of sampling weights
Daniel Westreich, Jessie K Edwards, Catherine R Lesko, Elizabeth Stuart, and Stephen R Cole · 2017
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Double/debiased machine learning for treatment and structural parameters, 2018
Victor Chernozhukov, Denis Chetverikov, Mert Demirer, Esther Duflo, Christian Hansen, Whitney Newey, and James Robins · 2018
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From sample average treatment effect to population average treatment effect on the treated: combining experimental with observational studies to estimate population treatment effects
Erin Hartman, Richard Grieve, Roland Ramsahai, and Jasjeet S Sekhon · 2015
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Doubly robust estimation of the local average treatment effect curve
Elizabeth L Ogburn, Andrea Rotnitzky, and James M Robins · 2015
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Combining randomized and non-randomized evidence in clinical research: a review of methods and applications
Pablo E Verde and Christian Ohmann · 2015
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Pragmatic trials
Ian Ford and John Norrie · 2016
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Semiparametric theory and empirical processes in causal inference
Edward H Kennedy · 2016
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A general procedure to combine estimators
Frédéric Lavancier and Paul Rochet · 2016
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Super-learning of an optimal dynamic treatment rule
Alexander R Luedtke and Mark J van der Laan · 2016
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Removing hidden confounding by experimental grounding
Nathan Kallus, Aahlad Manas Puli, and Uri Shalit · 2018
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Generalizing causal inferences from individuals in randomized trials to all trial-eligible individuals
Issa J Dahabreh, Sarah E Robertson, Eric J Tchetgen, Elizabeth A Stuart, and Miguel A Hernán · 2019
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Combining experimental and observational data to estimate treatment effects on long term outcomes
Susan Athey, Raj Chetty, and Guido Imbens · 2020
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Optimal doubly robust estimation of heterogeneous causal effects
Edward H Kennedy · 2020
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Combining observational and experimental datasets using shrinkage estimators
Evan Rosenman, Guillaume Basse, Art Owen, and Michael Baiocchi · 2020
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Shu Yang, Donglin Zeng, and Xiaofei Wang · 2020
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